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IMED2016 RasterStats Example
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| { | |
| "cells": [ | |
| { | |
| "cell_type": "code", | |
| "execution_count": 75, | |
| "metadata": { | |
| "collapsed": true | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "import geopandas\n", | |
| "import json\n", | |
| "from rasterstats import gen_zonal_stats\n", | |
| "from datetime import date\n", | |
| "from dateutil.relativedelta import relativedelta" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 13, | |
| "metadata": { | |
| "collapsed": true | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "countries = '/Users/mbertrand/Downloads/data/ne_10m_admin_0_countries/ne_10m_admin_0_countries.shp'\n", | |
| "airtemp = '/Volumes/Seagate/imed2016/UDELAWARE/air.mon.mean.v401.ll.PM1994_2014.tif'" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 14, | |
| "metadata": { | |
| "collapsed": true | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "# Band 1 is January 1994\n", | |
| "band_date = date(1994,1,1)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 79, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "Processing band 192 for 201001\n", | |
| "Processing band 193 for 201002\n", | |
| "Processing band 194 for 201003\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "# Create a dict of geopandas dataframes containing country info + mean air temp for the first 3 months of 2010\n", | |
| "\n", | |
| "band2010_start = (2010-1994)*12\n", | |
| "band2010_end = band2010_start + 3\n", | |
| "\n", | |
| "df_dict = {}\n", | |
| "for i in range(band2010_start,band2010_end):\n", | |
| " timestamp = (band_date + relativedelta(months=i)).strftime('%Y%m')\n", | |
| " print ('Processing band {} for {}'.format(i, timestamp))\n", | |
| " features = zonal_stats(countries, airtemp, band=i, stats=['mean'], geojson_out=True)\n", | |
| " df_dict[timestamp] = geopandas.GeoDataFrame.from_features(features)\n", | |
| " # Save to file for future reference\n", | |
| " with open('countries_air_{}.geojson'.format(timestamp), 'w') as f:\n", | |
| " f.write(df_dict[timestamp].to_json())\n", | |
| " " | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 80, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "[-2.5102562537560096, -5.01025625375601, -1.964102524977464]\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "# Get a list of mean air temperatures in Austria for each month\n", | |
| "\n", | |
| "austria_temps = [df[df['NAME'] == 'Austria']['mean'].values[0] for df in df_dict.values()]\n", | |
| "print austria_temps " | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "collapsed": true | |
| }, | |
| "outputs": [], | |
| "source": [] | |
| } | |
| ], | |
| "metadata": { | |
| "kernelspec": { | |
| "display_name": "Python 2", | |
| "language": "python", | |
| "name": "python2" | |
| }, | |
| "language_info": { | |
| "codemirror_mode": { | |
| "name": "ipython", | |
| "version": 2 | |
| }, | |
| "file_extension": ".py", | |
| "mimetype": "text/x-python", | |
| "name": "python", | |
| "nbconvert_exporter": "python", | |
| "pygments_lexer": "ipython2", | |
| "version": "2.7.11" | |
| } | |
| }, | |
| "nbformat": 4, | |
| "nbformat_minor": 0 | |
| } |
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